Clinical evaluation of autonomous, unsupervised planning integrated in MR-guided radiotherapy for prostate cancer

Künzel, Luise A.; Nachbar, Marcel; Hagmüller, Markus; Gani, Cihan; Boeke, Simon; Wegener, Daniel; Paulsen, Frank; Zips, Daniel; Thorwarth, Daniela

doi:10.1016/j.radonc.2022.01.036

Cited by 11 publications

(4 citation statements)

References 25 publications

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“…have successfully trained and validated a fast, accurate deep learning model for automated MRI segmentation ( 26 ). Additionally, efforts are underway to incorporate entirely autonomous workflows, encompassing automatic OAR contouring, target delineation, and automatic planning, within the clinical setting ( 27 ). This progress could alleviate the challenges of patient selection by streamlining the workflow in MR-guided radiation therapy, especially when treatment times become more comparable to non-adaptive radiotherapy.…”

Section: Discussionmentioning

confidence: 99%

Dosimetric benefit of online treatment plan adaptation in stereotactic ultrahypofractionated MR-guided radiotherapy for localized prostate cancer

Fink,

Buchele,

Baumann

et al. 2024

Front. Oncol.

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BackgroundApart from superior soft tissue contrast, MR-guided stereotactic body radiation therapy (SBRT) offers the chance for daily online plan adaptation. This study reports on the comparison of dose parameters before and after online plan adaptation in MR-guided SBRT of localized prostate cancer.Materials and methods32 consecutive patients treated with ultrahypofractionated SBRT for localized prostate cancer within the prospective SMILE trial underwent a planning process for MR-guided radiotherapy with 37.5 Gy applied in 5 fractions. A base plan, derived from MRI simulation at an MRIdian Linac, was registered to daily MRI scans (predicted plan). Following target and OAR recontouring, the plan was reoptimized based on the daily anatomy (adapted plan). CTV and PTV coverage and doses at OAR were compared between predicted and adapted plans using linear mixed regression models.ResultsIn 152 out of 160 fractions (95%), an adapted radiation plan was delivered. Mean CTV and PTV coverage increased by 1.4% and 4.5% after adaptation. 18% vs. 95% of the plans had a PTV coverage ≥95% before and after online adaptation, respectively. 78% vs. 100% of the plans had a CTV coverage ≥98% before and after online adaptation, respectively. The D0.2cc for both bladder and rectum were <38.5 Gy in 93% vs. 100% before and after online adaptation. The constraint at the urethra with a dose of <37.5 Gy was achieved in 59% vs. 93% before and after online adaptation.ConclusionOnline adaptive plan adaptation improves target volume coverage and reduces doses to OAR in MR-guided SBRT of localized prostate cancer. Online plan adaptation could potentially further reduce acute and long-term side effects and improve local failure rates in MR-guided SBRT of localized prostate cancer.

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Section: Discussionmentioning

confidence: 99%

Dosimetric benefit of online treatment plan adaptation in stereotactic ultrahypofractionated MR-guided radiotherapy for localized prostate cancer

Fink,

Buchele,

Baumann

et al. 2024

Front. Oncol.

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“…Automated treatment planning was implemented using particle swarm optimization (PSO), as described previously in detail by Künzel et al [31] , [32] , [33] . Plans were generated for a 1.5 T MR-Linac (Unity, Elekta AB, Sweden) using a 9-beam step and shoot intensity modulated radiotherapy technique with a maximum of 60 segments.…”

Section: Methodsmentioning

confidence: 99%

Full daily re-optimization improves plan quality during online adaptive radiotherapy

Tengler,

Künzel,

Hagmüller

et al. 2024

Physics and Imaging in Radiation Oncology

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“…In their study, the authors impressively showed that the whole treatment planning and delivery chain can be effectuated in one day. In the same way of thought, several recent studies have shown that fully automated contouring and RT planning is possible [14] , [15] , [16] , [17] . Future developments might therefore enable real-time annotation, planning and delivery.…”

mentioning

confidence: 92%

“…Xia et al [14] already showed the feasibility of a full-process solution for rectal cancer, integrating artificial intelligence based automated contouring and planning. For prostate cancer Künzel et al [15] , [16] proved that such automated tools can be combined to an autonomous treatment planning workflow without human interaction for reference plans in magnetic resonance guided radiotherapy. In such a way the treatment planning process would be accelerated in a scalable approach.…”

mentioning

confidence: 99%

Towards real-time radiotherapy planning: The role of autonomous treatment strategies

Künzel

Thorwarth²

2022

Physics and Imaging in Radiation Oncology

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Clinical evaluation of autonomous, unsupervised planning integrated in MR-guided radiotherapy for prostate cancer

Cited by 11 publications

References 25 publications

Dosimetric benefit of online treatment plan adaptation in stereotactic ultrahypofractionated MR-guided radiotherapy for localized prostate cancer

Dosimetric benefit of online treatment plan adaptation in stereotactic ultrahypofractionated MR-guided radiotherapy for localized prostate cancer

Full daily re-optimization improves plan quality during online adaptive radiotherapy

Towards real-time radiotherapy planning: The role of autonomous treatment strategies

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